Cover image for Panel Data Econometrics with R

Panel Data Econometrics with R

Author Giovanni Millo , Yves Croissant
Release Date: 2018/11/01
ISBN: 9781118949160
Topic:
0%
21
Chapters
0-1
Hours read
0k
Total Words
    Start Reading Now    
       Add to Wishlist       
View table of contents

Book Description

Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemiology, this book presents classic methodology and applications as well as more advanced topics and recent developments in this field including error component models, spatial panels and dynamic models. They have developed the software programming in R and host replicable material on the book’s accompanying website.

Table of Contents

  1. Cover
  2. Dedication
  3. Preface
  4. Acknowledgments
  5. About the Companion Website
  6. Chapter 1: Introduction
    1. 1.1 Panel Data Econometrics: A Gentle Introduction
    2. 1.2 R for Econometric Computing
    3. 1.3 plm for the Casual R User
    4. 1.4 plm for the Proficient R User
    5. 1.5 plm for the R Developer
    6. 1.6 Notations
  7. Chapter 2: The Error Component Model
    1. 2.1 Notations and Hypotheses
    2. 2.2 Ordinary Least Squares Estimators
    3. 2.3 The Generalized Least Squares Estimator
    4. 2.4 Comparison of the Estimators
    5. 2.5 The Two‐ways Error Components Model
    6. 2.6 Estimation of a Wage Equation
  8. Chapter 3: Advanced Error Components Models
    1. 3.1 Unbalanced Panels
    2. 3.2 Seemingly Unrelated Regression
    3. 3.3 The Maximum Likelihood Estimator
    4. 3.4 The Nested Error Components Model
  9. Chapter 4: Tests on Error Component Models
    1. 4.1 Tests on Individual and/or Time Effects
    2. 4.2 Tests for Correlated Effects
    3. 4.3 Tests for Serial Correlation
    4. 4.4 Tests for Cross‐sectional Dependence
  10. Chapter 5: Robust Inference and Estimation for Non‐spherical Errors
    1. 5.1 Robust Inference
    2. 5.2 Unrestricted Generalized Least Squares
  11. Chapter 6: Endogeneity
    1. 6.1 Introduction
    2. 6.2 The Instrumental Variables Estimator
    3. 6.3 Error Components Instrumental Variables Estimator
    4. 6.4 Estimation of a System of Equations
    5. 6.5 More Empirical Examples
  12. Chapter 7: Estimation of a Dynamic Model
    1. 7.1 Dynamic Model and Endogeneity
    2. 7.2 GMM Estimation of the Differenced Model
    3. 7.3 Generalized Method of Moments Estimator in Differences and Levels
    4. 7.4 Inference
    5. 7.5 More Empirical Examples
  13. Chapter 8: Panel Time Series
    1. 8.1 Introduction
    2. 8.2 Heterogeneous Coefficients
    3. 8.3 Cross‐sectional Dependence and Common Factors
    4. 8.4 Nonstationarity and Cointegration
  14. Chapter 9: Count Data and Limited Dependent Variables
    1. 9.1 Binomial and Ordinal Models
    2. 9.2 Censored or Truncated Dependent Variable
    3. 9.3 Count Data
    4. 9.4 More Empirical Examples
  15. Chapter 10: Spatial Panels
    1. 10.1 Spatial Correlation
    2. 10.2 Spatial Lags
    3. 10.3 Individual Heterogeneity in Spatial Panels
    4. 10.4 Serial and Spatial Correlation
  16. Bibliography
  17. Index
  18. End User License Agreement
18.218.254.122